On the rejection of internal and external disturbances in a wind energy conversion system with direct-driven PMSG

Li, Shengquan; Zhang, Kezhao; Li, Juan; Liu, Chao

doi:10.1016/j.isatra.2015.12.014

Cited by 63 publications

(46 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considering that the external complex environment and internal electromagnetic environment change is inevitable, the electromagnetic disturbance is generated in the process of the synchronous generator running and affected the current and rotational speed of wind turbine system, which can be described as additive white noises. In addition, the multiplicative noise disturbance is produced in the process of the rotor running, that is, the disturbance is coupled with the state of the system, which seriously affects the efficiency of the wind turbine . From what has been discussed above, the state space model of the FSCWT with disturbance can be described by system .…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The wind turbine systems work long term in the coastal, wilderness, plateau, and other places and exposure to harsh environmental conditions. Hence, the system disturbances usually include the vibration of wind turbine, electromagnetic disturbance, harmonic noise, environmental disturbance, and so on, 13,[37][38][39][40] which are typical multiple heterogeneous disturbances proposed in this paper.…”

Section: Application Example and Simulationmentioning

confidence: 99%

“…In addition, the multiplicative noise disturbance is produced in the process of the rotor running, that is, the disturbance is coupled with the state of the system, which seriously affects the efficiency of the wind turbine. 37,40 From what has been discussed above, the state space model of the FSCWT with disturbance can be described by system (1).…”

Section: Application Example and Simulationmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive disturbance observer‐based control for stochastic systems with multiple heterogeneous disturbances

Wei

Dong

Zhang

et al. 2019

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

Summary Antidisturbance control problem is discussed for stochastic systems with multiple heterogeneous disturbances, which include the white noise and the disturbance with unknown frequencies and amplitudes. An adaptive disturbance observer is designed to estimate the disturbance with unknown frequencies and amplitudes, based on which, an adaptive disturbance observer‐based control scheme is proposed by combining adaptive technique and linear matrix inequality method. It is proved that the closed‐loop system is asymptotically bounded in mean square when multiple heterogeneous disturbances exist simultaneously and that the equilibrium is globally asymptotically stable in probability as additive disturbance disappears. Finally, two simulation examples, including a wind turbine system, are given to show the effectiveness of the proposed scheme.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Section: Application Example and Simulationmentioning

confidence: 99%

Section: Application Example and Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive disturbance observer‐based control for stochastic systems with multiple heterogeneous disturbances

Wei

Dong

Zhang

et al. 2019

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…where v is defined as the angular velocity. According to Li et al, 20 the wind power coefficient C P can be obtained by the following equation…”

Section: The Wind Turbine Modelmentioning

confidence: 99%

“…Due to the features of the concise framework, convenient form for parameter tuning, analysis, and implementation, these kinds of linear ESO-based control methods have been broadly applied in dealing with dynamic uncertainties, disturbances, and nonlinear factors of the industrial systems. [16][17][18][19][20] In order to realize real-time speed control of a PMSG, it is necessary to measure the speed of the generator as the feedback signal. Compared with the current or voltage sensor, the cost of speed sensor detection accuracy is much more expensive.…”

Section: Introductionmentioning

confidence: 99%

Speed sensorless model predictive control method for a direct-drive wind energy conversion system

et al. 2019

Measurement and Control

Self Cite

View full text Add to dashboard Cite

Considering the problems of the internal and external disturbances of wind speed in the direct-drive wind energy conversion system based on a permanent magnet synchronous generator, a novel model predictive control based on the extended state observer method without the accurate mathematical system model is proposed in this paper. First, a model predictive control method is employed as the feedback controller, while the mathematical model of the control system can be adjusted online via the rolling optimization strategy. Second, an extended state observer is introduced to estimate the state variables and lumped disturbances, that is, the internal disturbances including nonlinear characteristic, multi-variety coupling effect, uncertainties of system parameters, and external disturbances including variations of wind speeds and uncertainties of the natural environment. Third, the effect of lumped disturbances can be attenuated by the estimated disturbance value via a feedforward channel. In addition, in order to achieve the real-time speed control performance of the permanent magnet synchronous generator, a speed sensorless algorithm based on a flux observer is proposed to solve the problem of unsuitability of mechanical speed sensor. Finally, the simulation results with several wind speed types show that the proposed sensorless model predictive control with the extended state observer strategy is an effective way to improve the performance of anti-disturbance and ability of tracking maximum wind energy of the wind power control system.

show abstract

Digital twin‐driven online intelligent assessment of wind turbine gearbox

Zhou,

Cui

et al. 2024

Wind Energy

View full text Add to dashboard Cite

Remaining useful fatigue life monitoring of wind turbine drivetrains is important. However, the implementation of real‐time monitoring often faces efficiency and accuracy challenges. In order to resolve this, this paper proposes a vibration‐based damage monitoring digital twin (VBDM‐DT) that enables the online intelligent evaluation of wind turbine gearboxes, using gear tooth surface durability as an example fatigue mode. The VBDM‐DT integrates a random wind load model, a high‐fidelity dynamics model, and a fatigue damage model. The random wind load model takes the wind speed from the supervisory control and data acquisition (SCADA) as input to estimate the input torque of the drivetrain in real time. Simultaneously, VBDM‐DT uses the vibration signals from the condition monitoring system (CMS) to intelligently calibrate the dynamics model, allowing it to be continuously adjusted and optimized in response to actual vibrations. The fatigue damage model takes the real‐time dynamic loads estimated by the high‐fidelity dynamic model as input to achieve real‐time fatigue damage monitoring of key components in the wind turbine gearbox. Applying the VBDM‐DT model to a 2 MW wind turbine gearbox, the results indicate that the model provides satisfactory accuracy in estimating input loads and good adaptability in intelligent calibration of the dynamic model. Based on this model, the fatigue life estimation for gears and bearings is more credible and reliable.

show abstract

On the rejection of internal and external disturbances in a wind energy conversion system with direct-driven PMSG

Cited by 63 publications

References 31 publications

Adaptive disturbance observer‐based control for stochastic systems with multiple heterogeneous disturbances

Adaptive disturbance observer‐based control for stochastic systems with multiple heterogeneous disturbances

Speed sensorless model predictive control method for a direct-drive wind energy conversion system

Digital twin‐driven online intelligent assessment of wind turbine gearbox

Contact Info

Product

Resources

About